1. Field of the Invention
The present invention relates to an indoor localization system that is energy efficient, and to a method of reducing power consumption of a radio badge in the indoor localization system, in which a sleep time for the radio badge is determined on the basis of a footstep count of a tracked target carrying the radio badge.
2. Description of the Related Art
Sensor network technologies have experienced significant advances in recent times. This has enabled a variety of applications for sensor networks in consumer electronics. For example, there is an ever-increasing number of commercial and experimental uses of sensor networks for object tracking, such as asset tracking in warehouses, patient monitoring in medical facilities, and using location to infer activities of daily living (ADL) at home.
Traditional localization research has concentrated on improving the accuracy of pinpointing the spatial position of a target. However, practical deployment of localization systems shows that positional accuracy and energy efficiency are of equal importance, especially in the context of sensor networks where energy is at a premium. Energy efficiency of mobile units (e.g., tags or badges) attached to tracked targets is critical for any practical deployment. A highly accurate localization system may be of little use if it requires frequent recharging of the mobile units. Therefore, both positional accuracy and energy efficiency are necessary in the design of localization systems.
Recent work addressed the issue of energy efficiency in localization systems. For example, it was found that in object-tracking sensor network systems, energy efficiency and positional accuracy are often two contradictory goals. By changing the sampling rate of location information, a localization system can trade higher energy consumption for better positional accuracy. Sampling rate here is defined as the rate at which the localization infrastructure and its mobile units are triggered to perform necessary communication and computation in determining positions. For example, sampling rate may be associated with the degree to which the mobile units emit radio signals for reception by the localization infrastructure. Furthermore, these systems have identified a number of basic energy-saving solutions that adaptively reduce the sampling rate with little impact on positional accuracy. Their general mechanisms are to (1) detect or predict the mobility pattern of a tracked target, and (2) then dynamically adjust the sampling rate according to a changing mobility pattern. For example, when a tracked target changes its position slowly, the sampling rate can be reduced for better energy conservation without losing much positional accuracy.
There are two main drawbacks in the existing solutions. First, current adaptation mechanisms, although dynamic, calculate the sampling rate based on heuristics. There is no formal analysis of positional error due to signal noise, communication delay, and sampling delay, which would, given the required positional error boundary specified by the applications, allow the system to derive the ideal sampling rate to provide sufficiently accurate position information, while minimizing the sampling rate, and in turn minimizing energy consumption.
Second, the mobility prediction of current solutions is based on the estimated position information. The velocity is obtained by taking the two most recent estimations and dividing the distance moved by the time elapsed. The predicted moving velocity is inherently inaccurate due to the position estimation errors. The adverse effect is particularly significant when the object is static. The network might continue to sample frequently, erroneously determining that the object is moving due to differences between consecutive position estimations.